How On-demand Analytics Service Works with Azure Data Lake

This article addresses how on-demand analytics service works with Azure Data Lake.

Azure Data Lake is an analytics service, which aims at easing big data analytics into a simpler avatar. This allows organizations to focus on managing, running and writing jobs instead of operating on a distributed infrastructure. Users use queries to extract valuable insights and transform their data, instead of configuring or deploying or tuning their hardware. This on-demand service can be used for handling job of big or small scale by making an estimate of their power requirement. Users just need to shell out for the service while it’s running, by making a cost-effective investment. The analytics service is also designed to cater to Azure Active Directory which allows users to manage roles and access, integrated with their on-premises organization’s identity system in an effective manner.

On-demand Analytics Service Works with Azure Data Lake

It also comes with U-SQL language, which unifies goodness of SQL elegantly with user codes expressive power. The scalable distribution of U-SQL allows users to make sense of data across different SQL servers as well as in the store.

Capabilities of Azure Data Lake

Dynamic Scaling

One can consider Data Lake analytics as specifically designed to boost performance while working on a cloud scale. It provides resources dynamically and allows users to perform analytics operations on terabytes of data. It winds resources automatically, so user is only paying for the resource which is being used. Users can work more efficiently towards their organizational goals by focusing their attention on the logic and leaving the processing and storage part to the Data Lake.

Develop Faster and Optimize Effectively

Data Lake Analytics is seamlessly aligned with Visual Studio, offering known tools for debugging, running or tuning a code. U-SQL’s Visualization helps the users in how their code works at a higher scale, which helps in easily identifying the performance related issues and it can also be used for optimizing costs.

U-SQL – Powerful and Simple

Data Lake Analytics comes with U-SQL language that is simple to use and comes with an essence of familiarity. It is also designed to work with big data, which makes itso efficient on Data Lake.

IT investments for seamless integrations

Data Lake Analytics can effectively use users existing investments for identifying, securing, managing and data warehousing tasks. It essentially eases data governance while making it easier for the user to extend their existing data applications in quick time. Data Lake Analytics boasts of built-in monitoring features and auditing elements that works according to user permission and management through its integrated Active Directory.

Cost Effective and Affordable

Data Lake Analytics is an affordable, cost-effective service for working on a real world big data scenario. Users pay depending on the service’s operation time, and the service infrastructure with intelligence that it automatically cuts the power as soon as the task is complete. This ensures that the user is only charged for power which is being used in performing his/her tasks. The user also doesn’t have to spend on any sort of license, hardware or agreement to consume their services.

Access your complete Azure Database

Data Lake Analytics works best with Azure Data, promising top grade level of output and performance while offering parallelization for big data real world workloads. Itcan also be effectively used with Azure SQL Database and Azure Blob Storage.

With drastic improvements made in the latest SQL Server editions, one can make the mistake of thinking the application as flawless. Unfortunately it is hardly so and it still makes great sense to invest in a sql recovery tool.

Author Introduction:

Victor Simon is a data recovery expert in DataNumen, Inc., which is the world leader in data recovery technologies, including access recovery and sql recovery software products. For more information visit

Leave a Reply

Your email address will not be published. Required fields are marked *